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--- |
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license: other |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: segformer-finetuned-4ss1st3r_s3gs3m_24Jan_all-10k-steps |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# segformer-finetuned-4ss1st3r_s3gs3m_24Jan_all-10k-steps |
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This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3095 |
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- Mean Iou: 0.5513 |
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- Mean Accuracy: 0.7874 |
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- Overall Accuracy: 0.9260 |
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- Accuracy Bg: nan |
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- Accuracy Fallo cohesivo: 0.9668 |
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- Accuracy Fallo malla: 0.6808 |
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- Accuracy Fallo adhesivo: 0.9727 |
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- Accuracy Fallo burbuja: 0.5291 |
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- Iou Bg: 0.0 |
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- Iou Fallo cohesivo: 0.9167 |
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- Iou Fallo malla: 0.6189 |
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- Iou Fallo adhesivo: 0.7307 |
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- Iou Fallo burbuja: 0.4903 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 1337 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: polynomial |
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- training_steps: 10000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Bg | Accuracy Fallo cohesivo | Accuracy Fallo malla | Accuracy Fallo adhesivo | Accuracy Fallo burbuja | Iou Bg | Iou Fallo cohesivo | Iou Fallo malla | Iou Fallo adhesivo | Iou Fallo burbuja | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:-----------:|:-----------------------:|:--------------------:|:-----------------------:|:----------------------:|:------:|:------------------:|:---------------:|:------------------:|:-----------------:| |
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| 0.1378 | 1.0 | 783 | 0.2677 | 0.4895 | 0.7143 | 0.9122 | nan | 0.9724 | 0.5531 | 0.9663 | 0.3654 | 0.0 | 0.9038 | 0.5327 | 0.6757 | 0.3351 | |
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| 0.1117 | 2.0 | 1566 | 0.2305 | 0.5289 | 0.7978 | 0.9246 | nan | 0.9507 | 0.7727 | 0.9705 | 0.4974 | 0.0 | 0.9214 | 0.6808 | 0.5876 | 0.4549 | |
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| 0.0881 | 3.0 | 2349 | 0.2041 | 0.5556 | 0.7867 | 0.9354 | nan | 0.9712 | 0.7391 | 0.9389 | 0.4975 | 0.0 | 0.9273 | 0.6790 | 0.7323 | 0.4394 | |
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| 0.0878 | 4.0 | 3132 | 0.1984 | 0.5584 | 0.8003 | 0.9346 | nan | 0.9556 | 0.8247 | 0.9602 | 0.4606 | 0.0 | 0.9261 | 0.6935 | 0.7373 | 0.4352 | |
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| 0.0895 | 5.0 | 3915 | 0.2841 | 0.5246 | 0.8086 | 0.9088 | nan | 0.9137 | 0.8834 | 0.9719 | 0.4652 | 0.0 | 0.8964 | 0.6309 | 0.6593 | 0.4365 | |
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| 0.0773 | 6.0 | 4698 | 0.2547 | 0.5652 | 0.7823 | 0.9336 | nan | 0.9775 | 0.6843 | 0.9384 | 0.5291 | 0.0 | 0.9251 | 0.6378 | 0.7820 | 0.4813 | |
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| 0.0667 | 7.0 | 5481 | 0.2726 | 0.5609 | 0.7932 | 0.9295 | nan | 0.9741 | 0.6609 | 0.9689 | 0.5689 | 0.0 | 0.9203 | 0.6202 | 0.7548 | 0.5093 | |
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| 0.0678 | 8.0 | 6264 | 0.2950 | 0.5276 | 0.8002 | 0.9175 | nan | 0.9443 | 0.7561 | 0.9713 | 0.5292 | 0.0 | 0.9089 | 0.6570 | 0.5900 | 0.4822 | |
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| 0.0653 | 9.0 | 7047 | 0.2712 | 0.5467 | 0.7682 | 0.9288 | nan | 0.9690 | 0.6971 | 0.9641 | 0.4425 | 0.0 | 0.9189 | 0.6330 | 0.7588 | 0.4228 | |
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| 0.0646 | 10.0 | 7830 | 0.2841 | 0.5499 | 0.7819 | 0.9272 | nan | 0.9681 | 0.6840 | 0.9688 | 0.5068 | 0.0 | 0.9178 | 0.6243 | 0.7345 | 0.4728 | |
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| 0.057 | 11.0 | 8613 | 0.3373 | 0.5257 | 0.7782 | 0.9166 | nan | 0.9593 | 0.6555 | 0.9739 | 0.5242 | 0.0 | 0.9075 | 0.6040 | 0.6319 | 0.4848 | |
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| 0.0591 | 12.0 | 9396 | 0.3082 | 0.5504 | 0.7900 | 0.9247 | nan | 0.9656 | 0.6776 | 0.9705 | 0.5463 | 0.0 | 0.9148 | 0.6172 | 0.7182 | 0.5019 | |
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| 0.053 | 12.77 | 10000 | 0.3095 | 0.5513 | 0.7874 | 0.9260 | nan | 0.9668 | 0.6808 | 0.9727 | 0.5291 | 0.0 | 0.9167 | 0.6189 | 0.7307 | 0.4903 | |
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### Framework versions |
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- Transformers 4.31.0.dev0 |
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- Pytorch 2.0.1+cpu |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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